PyMC Samplers
CommunityMaster PyMC sampling for fast, reliable models.
Authorbenmaier
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Helps data scientists optimize Bayesian inference by selecting and configuring PyMC sampling methods to ensure reliable and efficient posterior exploration.
Core Features & Use Cases
- NUTS, HMC, and Metropolis variants for flexible sampling across continuous and discrete models
- Customizable step methods, initialization, and convergence diagnostics to improve reliability
- Example: Compare NUTS and Metropolis on a hierarchical Bayesian model to evaluate convergence and efficiency
Quick Start
Provide a PyMC model and call pm.sample with your desired settings to begin posterior inference.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: PyMC Samplers Download link: https://github.com/benmaier/decision-agent-placeholder/archive/main.zip#pymc-samplers Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
Agent Skills Search Helper
Install a tiny helper to your Agent, search and equip skill from 471,000+ vetted skills library on demand.